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Iranian Journal of Medical Sciences، جلد ۴۸، شماره ۱، صفحات ۳۵-۴۲
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عنوان انگلیسی Identification of Key Genes and Biological Pathways Related to Myocardial Infarction through Integrated Bioinformatics Analysis
چکیده انگلیسی مقاله Background: Coronary heart disease is the leading cause of death worldwide. Myocardial infarction (MI) is a fatal manifestation of coronary heart disease, which can present as sudden death. Although the molecular mechanisms of coronary heart disease are still unknown, global gene expression profiling is regarded as a useful approach for deciphering the pathophysiology of this disease and subsequent diseases. This study used a bioinformatics analysis approach to better understand the molecular mechanisms underlying coronary heart disease.Methods: This experimental study was conducted in the department of cardiology, Aja University of Medical Sciences (2021-2022), Tehran, Iran. To identify the key deregulated genes and pathways in coronary heart disease, an integrative approach was used by merging three gene expression datasets, including GSE19339, GSE66360, and GSE29111, into a single matrix. The t test was used for the statistical analysis, with a significance level of P< 0.05. Results: The limma package in R was used to identify a total of 133 DEGs, consisting of 124 upregulated and nine downregulated genes. KDM5D, EIF1AY, and CCL20 are among the top upregulated genes. Moreover, the interleukin 17 (IL-17) signaling pathway and four other signaling pathways were identified as the potent underlying pathogenesis of both coronary artery disease (CAD) and MI using a systems biology approach. Accordingly, these findings can provide expression signatures and potential biomarkers in CAD and MI pathophysiology, which can contribute to both diagnosis and therapeutic purposes.Conclusion: Five signaling pathways were introduced in MI and CAD that were primarily involved in inflammation, including the IL-17 signaling pathway, TNF signaling pathway, toll-like receptor signaling pathway, C-type lectin receptor signaling pathway, and rheumatoid arthritis signaling pathway.
کلیدواژه‌های انگلیسی مقاله myocardial infarction, Coronary disease, bioinformatics
نویسندگان مقاله Nader Ebadi |
Department of Cardiology, School of Medicine, Aja University of Medical Sciences, Tehran, Iran

Reza Arefizadeh |
Department of Cardiology, School of Medicine, Aja University of Medical Sciences, Tehran, Iran

Mehrdad Nasrollahzadeh Sabet |
Department of Cardiology, School of Medicine, Aja University of Medical Sciences, Tehran, Iran

Naser Goodarzi |
Department of Clinical Psychology, School of Medicine, Aja University of Medical Sciences, Tehran, Iran

نشانی اینترنتی https://ijms.sums.ac.ir/article_48663_acd8997b81181d23dcb1bbb77e1e1a41.pdf
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